1,427 research outputs found
Human inference beyond syllogisms: an approach using external graphical representations.
Research in psychology about reasoning has often been restricted to relatively inexpressive statements involving quantifiers (e.g. syllogisms). This is limited to situations that typically do not arise in practical settings, like ontology engineering. In order to provide an analysis of inference, we focus on reasoning tasks presented in external graphic representations where statements correspond to those involving multiple quantifiers and unary and binary relations. Our experiment measured participants' performance when reasoning with two notations. The first notation used topological constraints to convey information via node-link diagrams (i.e. graphs). The second used topological and spatial constraints to convey information (Euler diagrams with additional graph-like syntax). We found that topo-spatial representations were more effective for inferences than topological representations alone. Reasoning with statements involving multiple quantifiers was harder than reasoning with single quantifiers in topological representations, but not in topo-spatial representations. These findings are compared to those in sentential reasoning tasks
Deductive reasoning about expressive statements using external graphical representations
Research in psychology on reasoning has often been restricted to relatively inexpressive statements involving quantifiers. This is limited to situations that typically do not arise in practical settings, such as ontology engineering. In order to provide an analysis of inference, we focus on reasoning tasks presented in external graphic representations where statements correspond to those involving multiple quantifiers and unary and binary relations. Our experiment measured participantsâ performance when reasoning with two notations. The first used topology to convey information via node-link diagrams (i.e. graphs). The second used topological and spatial constraints to convey information (Euler diagrams with additional graph-like syntax). We found that topological- spatial representations were more effective than topological representations. Unlike topological-spatial representations, reasoning with topological representations was harder when involving multiple quantifiers and binary relations than single quantifiers and unary relations. These findings are compared to those for sentential reasoning tasks
Compositional Performance Modelling with the TIPPtool
Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations
Trace Spaces: an Efficient New Technique for State-Space Reduction
State-space reduction techniques, used primarily in model-checkers, all rely
on the idea that some actions are independent, hence could be taken in any
(respective) order while put in parallel, without changing the semantics. It is
thus not necessary to consider all execution paths in the interleaving
semantics of a concurrent program, but rather some equivalence classes. The
purpose of this paper is to describe a new algorithm to compute such
equivalence classes, and a representative per class, which is based on ideas
originating in algebraic topology. We introduce a geometric semantics of
concurrent languages, where programs are interpreted as directed topological
spaces, and study its properties in order to devise an algorithm for computing
dihomotopy classes of execution paths. In particular, our algorithm is able to
compute a control-flow graph for concurrent programs, possibly containing
loops, which is "as reduced as possible" in the sense that it generates traces
modulo equivalence. A preliminary implementation was achieved, showing
promising results towards efficient methods to analyze concurrent programs,
with very promising results compared to partial-order reduction techniques
Verified AIG Algorithms in ACL2
And-Inverter Graphs (AIGs) are a popular way to represent Boolean functions
(like circuits). AIG simplification algorithms can dramatically reduce an AIG,
and play an important role in modern hardware verification tools like
equivalence checkers. In practice, these tricky algorithms are implemented with
optimized C or C++ routines with no guarantee of correctness. Meanwhile, many
interactive theorem provers can now employ SAT or SMT solvers to automatically
solve finite goals, but no theorem prover makes use of these advanced,
AIG-based approaches.
We have developed two ways to represent AIGs within the ACL2 theorem prover.
One representation, Hons-AIGs, is especially convenient to use and reason
about. The other, Aignet, is the opposite; it is styled after modern AIG
packages and allows for efficient algorithms. We have implemented functions for
converting between these representations, random vector simulation, conversion
to CNF, etc., and developed reasoning strategies for verifying these
algorithms.
Aside from these contributions towards verifying AIG algorithms, this work
has an immediate, practical benefit for ACL2 users who are using GL to
bit-blast finite ACL2 theorems: they can now optionally trust an off-the-shelf
SAT solver to carry out the proof, instead of using the built-in BDD package.
Looking to the future, it is a first step toward implementing verified AIG
simplification algorithms that might further improve GL performance.Comment: In Proceedings ACL2 2013, arXiv:1304.712
Towards spatial reasoning on building information models
The paper presents a conceptual study on the application of spatial reasoning on building information models. In many cases, building regulations and client demands imply traints on the building design with inherent spatial semantics. If we are able to represent these spatial constraints in a computerinterpretable way, the building design can be checked for fulfilling them. In this context, spatial reasoning technology can be applied in two different ways. First, we can check the consistency of the spatial constraints in effect, i.e. find out whether there are contradictions between them. Second, we can check whether a concrete building design is compliant with these constraints. The paper gives a detailed overview on the currently available spatial calculi and introduces two possible implementation pproaches
The mechanism underlying backward priming in a lexical decision task: Spreading activation versus semantic matching
Koriat (1981) demonstrated that an association from the target to a preceding prime, in the absence of an association from the prime to the target, facilitates lexical decision and referred to this effect as "backward priming". Backward priming is of relevance, because it can provide information about the mechanism underlying semantic priming effects. Following Neely (1991), we distinguish three mechanisms of priming: spreading activation, expectancy, and semantic matching/integration. The goal was to determine which of these mechanisms causes backward priming, by assessing effects of backward priming on a language-relevant ERP component, the N400, and reaction time (RT). Based on previous work, we propose that the N400 priming effect reflects expectancy and semantic matching/integration, but in contrast with RT does not reflect spreading activation. Experiment 1 shows a backward priming effect that is qualitatively similar for the N400 and RT in a lexical decision task. This effect was not modulated by an ISI manipulation. Experiment 2 clarifies that the N400 backward priming effect reflects genuine changes in N400 amplitude and cannot be ascribed to other factors. We will argue that these backward priming effects cannot be due to expectancy but are best accounted for in terms of semantic matching/integration
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